In India, human population has increased six-fold from 200 million to 1200 million that coupled with economic growth has resulted in significant land use and land cover (LULC) changes during 1880–2010. However, large discrepancies in the existing LULC datasets have hindered our efforts to better understand interactions among human activities, climate systems, and ecosystem in India. In this study, we incorporated high-resolution remote sensing datasets from Resourcesat-1 and historical archives at district (N = 590) and state (N = 30) levels to generate LULC datasets at 5 arc minute resolution during 1880–2010 in India. Results have shown that a significant loss of forests (from 89 million ha to 63 million ha) has occurred during the study period. Interestingly, the deforestation rate was relatively greater under the British rule (1880–1950s) and early decades after independence, and then decreased after the 1980s due to government policies to protect the forests. In contrast to forests, cropland area has increased from 92 million ha to 140.1 million ha during 1880–2010. Greater cropland expansion has occurred during the 1950–1980s that coincided with the period of farm mechanization, electrification, and introduction of high yielding crop varieties as a result of government policies to achieve self-sufficiency in food production. The rate of urbanization was slower during 1880–1940 but significantly increased after the 1950s probably due to rapid increase in population and economic growth in India. Our study provides the most reliable estimations of historical LULC at regional scale in India. This is the first attempt to incorporate newly developed high-resolution remote sensing datasets and inventory archives to reconstruct the time series of LULC records for such a long period in India. The spatial and temporal information on LULC derived from this study could be used by ecosystem, hydrological, and climate modeling as well as by policy makers for assessing the impacts of LULC on regional climate, water resources, and biogeochemical cycles in terrestrial ecosystemsRead More

India is the world’s tenth most forested nation with 76.87 M ha of forest and tree cover occupying 23.4% of its geographical area. Forests—with their intrinsic of carbon sequestration and storage values—are in the front line of India’s climate change mitigation strategies. This paper provides estimates of sequestered carbon in India’s forest and tree cover for the years 1995 and 2005 as per the IPCC good practice guidelines method. It is based on the primary data for the soil carbon pool through collecting soil samples by laying out quadrats across the country and secondary data for the growing stock of all forest and tree cover in the country. The estimates are compared with current and future projected emissions. It is found that conservation policies have resulted in increase of the country’s forest carbon stocks from 6244.8 to 6621.6 Mt with an annual increment of 37.7 Mt of the carbon from 1995 to 2005. Annual CO 2 removal by the forests is enough to neutralise 9.3% of the country’s 2000 level emissions. Continued removals by the forest and tree cover would offset 6.5 and 4.9% of India’s projected annual emissions in 2010 and 2020 respectively. Economically, the annual value of this forest carbon in the international market is about USRead More

Abstract. Flood is one of the most the most re-occurring natural hazard in the state of Bihar, as well as in India. The major rivers responsible for flood in the state of Bihar are Kosi, Gandak, Ghagra and Bagmati, which are the tributary rivers of Ganges. The head water catchment area of these rivers lies in the Himalayan state of Nepal. The high rainfall in Nepal, siltation of hydraulic structures, rivers and low topography of North Bihar causes flood occurrence in these areas on regular basis. Remote sensing and GIS plays an important role in mapping, monitoring and providing spatial database for all flood related studies. The present work focuses on the use remote sensing based topography and images in GIS environment for integrated flood study of Bagmati River, which is one of the most flood prone rivers of North Bihar. The Digital Elevation Model (DEM) from shuttle radar topography mission (SRTM) was used to create detailed sub-basin and river network map of entire Bagmati basin. The floods of July–August 2002 were mapped using RADARSAT-1 data using threshold based method. The SRTM DEM and ground based river cross-section from Dheng to Benibad stretch of Bhagmati River were used to create 1-dimensional hydrodynamic (1-D HD) model for simulating flood water level, discharge and flood inundation. Validation of simulated flood flows was done using observed water level of central water commission (CWC) from Dheng to Runisaidpur stations, with coefficient of correlation of 0.85. Finally, an integrated framework for flood modelling and management system is proposedRead More